Senior Product Manager - Autonomous Agents

Own the Autonomous Agents roadmap end-to-end: problem discovery, prioritization, spec writing, delivery coordination, and outcome tracking.

Translate enterprise customer and partner needs into product requirements, working closely with Customer Success, Delivery, and Sales/RevOps.

Partner with Applied Research and Data Science to define evaluation criteria, benchmark programs, and quality gates for agentic AI capabilities.

Drive cross-functional alignment across Engineering (Runtime, Studio, Channels, SDKs), QA, and Delivery on scope, dependencies, and launch readiness.

Establish instrumentation requirements and ensure every shipped agent capability has the telemetry needed to measure usage, reliability, and outcomes.

Run planning and execution cadence: quarterly roadmap inputs, monthly scope lock, weekly execution reviews, and launch readiness sign-offs.

Drive post-release learning: monitoring windows, post-incident reviews (PIRs), and systematic feedback loops into roadmap planning.

Engineering degree with 5+ years of progressive product management experience; an MBA from a Tier 1 institute is a plus.

Proven ownership of a complex, multi-surface product area with demonstrated delivery of technical features to enterprise customers.

Deep understanding of conversational AI and agentic systems, including:

LLM-based reasoning, tool calling, and multi-step task execution.

Agent orchestration patterns (supervisor/sub-agent, planning loops, HITL escalation).

Evaluation methodologies for AI systems: task completion, goal accuracy, regression, and drift.

Production observability for AI agents: tracing, logging, alerting, and failure analysis.

Strong technical fluency: APIs, distributed systems, cloud environments, and AI/ML deployment workflows.

Excellent stakeholder leadership and executive communication; ability to drive alignment across research, engineering, and GTM without direct authority.

Customer-first mindset with experience translating enterprise customer needs into clear, actionable product requirements.

Experience building or shipping AI agent products at a conversational AI, NLU, or enterprise AI platform company.

Familiarity with agentic frameworks and protocols (e.g., LangChain, LangGraph, Model Context Protocol, OpenAI function calling, tool-use patterns).

Experience supporting regulated or mission-critical environments (financial services, airlines/telephony, healthcare, payments).

Experience working with large SI/partner ecosystems and coordinating enablement and customer success programs.

Background in or strong familiarity with progressive delivery (feature flags, canary rollouts), incident management, and post-incident learning disciplines.